In recent years, active noise reduction devices have been put in practical use. Such an active noise reduction device cancels a noise that is generated during an operation (drive) of an apparatus, such as an automobile, in a passenger compartment, and reduces the noise audible to a driver and a passenger. FIG. 22 is a block diagram of conventional active noise reduction system 901 for reducing noise N0 that is audible in space S1, such as a passenger compartment of an automobile. Conventional active noise reduction system 901 includes reference signal source 1, cancel sound source 2, error signal source 3, and active noise reduction device 904.
Reference signal source 1 outputs a reference signal x(i) that has a correlation with noise N0. Active noise reduction device 904 has the reference signal x(i) input thereto, and outputs a cancel signal y(i). Cancel sound source 2 outputs cancel sound N1 corresponding to the cancel signal y(i) into space S1, such as the passenger compartment. Error signal source 3 outputs an error signal e(i) corresponding to a residual sound caused by interference between noise N0 and cancel sound N1 in space S1.
Active noise reduction device 904 includes adaptive filter (hereinafter, ADF) 905, simulated acoustic transfer characteristic data filter (hereinafter, Chat) 6, and least mean square operation unit (hereinafter, LMS operation unit) 907. Active noise reduction device 904 operates at discrete time intervals of a sampling period Ts.
ADF 905 includes a finite impulse response (hereinafter, FIR) type adaptive filter composed of N filter coefficients w(k) with values updated every sampling period Ts (where k=0, 1, . . . , N−1). The current filter coefficient w(k,n) is updated by a filtered X-LMS (hereinafter, FxLMS) algorithm. ADF 905 outputs the current cancel signal y(n) by using the filter coefficient w(k,n) and the reference signal x(i). In other words, ADF 905 determines the cancel signal y(n) by performing a filtering operation, that is, a convolution operation expressed by Formula 1. In this description, the current time is an n-th step. Accordingly, a next time (or a next point in time) is a (n+1)-th step, and a last time is a (n−1)-th step.
                              y          ⁡                      (            n            )                          =                              ∑                          k              =              0                                      N              -              1                                ⁢                                          ⁢                                    w              ⁡                              (                                  k                  ,                  n                                )                                      ·                          x              ⁡                              (                                  n                  -                  k                                )                                                                        (                  Formula          ⁢                                          ⁢          1                )            
Chat 6 has an FIR type filter composed of a time-invariant filter coefficient (hereinafter, simulated acoustic transfer characteristic data) C^ that simulates an acoustic transfer characteristic C(i) of a signal transfer path of the cancel signal y(i). The signal transfer path mentioned here refers to a transfer path from output of the cancel signal y(i) to arrival of the error signal e(i) at LMS operation unit 907. Chat 6 outputs a filtered reference signal r(i) obtained by performing a filtering operation on the simulated acoustic transfer characteristic data C^ and the reference signal x(i).
LMS operation unit 907 updates a current filter coefficient W(n) of ADF 905 by using a current filtered reference signal R(n), the error signal e(n), and a step size parameter μ. LMS operation unit 907 then calculates the next-step filter coefficient W(n+1), as expressed by Formula 2.W(n+1)=W(n)−μ·e(n)·R(n)  (Formula 2)
Here, the filter coefficient W(n) of ADF 905 is a vector with N rows and one column, as expressed by Formula 3, and is composed of N current filter coefficients w(k,n).W(n)=[w(0,n),w(1,n), . . . ,w(N−1,n)]T  (Formula 3)
The filtered reference signal R(n) is also a vector with N rows and one column, and is composed of N filtered reference signals r(i) from the current time to the past by (N−1) steps.
Active noise reduction system 901 updates the filter coefficient W(i) of ADF 905 every sampling period Ts, as expressed by Formula 2. As a result, active noise reduction system 901 outputs the cancel signal y(i) for canceling noise N0 at a position of error signal source 3.
A conventional active noise reduction system similar to active noise reduction system 901 is described in PTL 1.
In conventional active noise reduction device 904, if a level of noise N0 decreases, cancel sound N1 that is output from cancel sound source 2 may become larger than noise N0, and thus cancel sound N1 may become an abnormal sound.